Cloud security shared responsibility model

Based on the well-established cloud security shared responsibility model, clients and cloud service providers are both responsible for cloud security. The cloud service providers are responsible for the security “of the cloud,” while clients are responsible for security “in the cloud.” However, the extent of clients’ responsibility depends on the consumption model.

For the most part, the cloud service provider infrastructure is secure. However, there is a possibility of client-side data security issues, including cybersecurity and workload problems. Cloud misconfigurations happen when cloud security settings are not properly configured, creating vulnerabilities that can be leveraged by external attackers using ransomware or insider threat actors exploiting security gaps.

Understand compliance monitoring

As a general rule, organizations can benefit from enacting access control by using data encryption and conducting regular audits. They should also establish compliance programs to address ongoing alignment with security controls. Cloud security standards should be implemented to address cloud services needs in meeting those relevant requirements issued by state and federal governments and industry standards. In addition, internal policies should provide critical guardrails for cloud security.

Understanding the cloud security standards for your cloud business estate and what additional protections would benefit your IT environment is critical. The ongoing management of cloud environment protection supports ongoing success. Many organizations perform periodic audits of their cloud security compliance posture only to find that misconfigurations have crept in. Human error is typically to blame, so having a continuous controls compliance monitoring solution to attend to applicable cloud security requirements is vital to catch these misconfigurations as they arise in real-time.

Use gen AI to improve cloud security

As the world moves to embrace generative artificial intelligence (gen AI) for various use cases, there is an opportunity to use this emerging technology to improve cybersecurity protections in the cloud. Cloud security standards are a critical component of an organization’s cybersecurity protections. Using AI technology to establish, monitor and manage the cloud security controls within an organization’s cloud estate should be designed to protect against human-caused misconfigurations and provide reporting against compliance to cloud security requirements.

There are three main ways to improve cloud security posture by establishing continuous controls monitoring capabilities using gen AI:

• Deployment: Cloud security standards can be translated by AI to enable seamless deployment of protective and detective cloud security controls, which would lead to improved productivity and compliance to such requirements.
• Management: An AI model can be trained to continuously learn about the environment, provide up-to-date changes to the cloud security posture controls and respond quickly to any detected concerns.
• Threat Detection: An AI model can also be trained to detect, correlate and align cloud security standards with threats and automatic and semi-automatic response capabilities for real-time action and analysis.

Point security solutions help manage companies’ posture management for the cloud, and they will continue to be part of a cybersecurity toolbox that companies can utilize. However, static tools do not adapt in real time. Rather, a continuous controls monitoring solution using gen AI demonstrates being the ideal solution, where IT environments are compliant with the latest cloud security standards and can adapt to misconfiguration drift as it occurs, automatically correcting for high-risk exposures.

Flexible cyber defense with gen AI

Because a continuous controls monitoring solution is dynamic and self-healing, its capabilities should accelerate the deployment of cloud security controls that align with company policies. It would also improve security operations by providing visibility into cloud assets and activity across multiple cloud providers. Meanwhile, in the event of a security breach, the AI solution would identify threats and accelerate investigations through behavior analytics, data flow and vulnerability analysis.

If used properly, AI can be harnessed to help drive more effective cybersecurity controls, addressing compliance and improving overall cyber risk management and oversight in the cloud.

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The Cybersecurity and Infrastructure Security Agency (CISA) and National Security Agency (NSA) have recently released new CSI (Cybersecurity Information) sheets aimed at providing information and guidelines to organizations on how to effectively secure their cloud environments.

This new release includes a total of five CSI sheets, covering various aspects of cloud security such as threat mitigation, identity and access management, network security and more. Here’s our overview of the new CSI sheets, what they address and the key takeaways from each.

Implementing cloud identity and access management

The “Use Secure Cloud Identity and Access Management Practices” CSI sheet was created to help identify and address the unique security challenges presented in cloud environments. With most modern businesses quickly adopting more cloud-based solutions to help them scale, the virtual attack surface they create needs adequate protection.

The document goes on to explain that one of the major risks associated with expanding into the cloud comes from malicious cyber actors who actively exploit undiscovered vulnerabilities in third-party platform access protocols. This is primarily due to misconfigurations in user access restrictions or role definitions, as well as the strategic execution of social engineering campaigns.

Many of the risks identified can be successfully mitigated through the use of Identity and Access Management (IAM) solutions designed to monitor and control cloud access more strictly. In addition, the CISA and NSA recommend proper implementation of multifactor authentication protocols, which are particularly effective when improving phishing resistance, as well as the careful management of public key infrastructure certificates.

Another important point mentioned is the use of encrypted channels for users when accessing cloud resources. It’s suggested that organizations mandate the use of Transport Layer Security (TLS) 1.2 or higher as well as relying on the Commercial National Security Algorithm (CNSA) Suite 2.0 whenever possible when configuring all software and firmware.

Hardening cloud key management processes

The “Use Secure Cloud Key Management Practices” sheet was released to reinforce the important role that cryptographic operations play in cloud environments. These operations keep communications secure and provide the right levels of encryption for data both in motion and at rest.

The sheet outlines the various key management options available to cloud customers, including Cloud Service Provider (CSP) managed encryption keys and third-party Key Management Solutions (KMS) that can and should be applied.

Having a dedicated hardware security module (HSM) is another important component of applying adequate key management processes, as it provides a secure and tamper-resistant environment for storing and processing cryptographic keys.

However, organizations will want to weigh the benefits and risks associated with having shared, partitioned and dedicated HSMs in place since a shared responsibility model will need to be applied to both the organization and the third parties they’re working with.

Utilizing network segmentation and encryption

The “Implement Network Segmentation and Encryption in Cloud Environments” sheet was designed to highlight the ongoing shift from perimeter-based security approaches to more granular, identity-based network security. To do this safely, the CISA and NSA recommend using end-to-end encryption and micro-segmentation to isolate and harden their networks from quick-scaling cyberattacks.

Currently, the NSA-approved CNSA Suite algorithms or NIST-recommended algorithms are considered the gold standard for data in transit encryption. These are recommended numerous times throughout all of the sheets provided, and private connectivity versus public connectivity is relied on whenever possible when connecting to cloud services.

Because of how aggressive many modern-day cyberattacks are, implementing network segmentation is highly recommended. This helps to contain breaches that would otherwise move laterally across connected databases or critical systems. There are now many cloud-native options to help organizations implement segmentation and accurately control traffic flows across the network.

Securing data in the cloud

The “Secure Data in the Cloud” sheet provided goes into detail about the classification of cloud data types, including “File,” “Object” and “Block” storage options. The sheet goes on to explain that depending on the type of storage you’re using, this will mean applying diverse measures to properly secure it.

Regardless of the encryption being used for each type of data, it is strongly advised to reduce the use of public networks when accessing cloud services. These are constant sources of security vulnerabilities, as public networks have very limited security in place and are often used by malicious sources to monitor traffic and find weaknesses in device security.

This sheet also stresses the implementation of role-based access control (RBAC) and attribute-based access control (ABAC) as an effective way to manage specific data access. These solutions allow you to see very granular access permissions while also encouraging organizations to eliminate overly permissive cloud access policies.

A big part of maximizing security in the cloud is reviewing and understanding the procedures and policies of cloud service providers, specifically how they apply to data storage and retention.

Businesses can work with their CSPs to implement solutions like “soft deletion,” which is the practice of marking data as deleted without actually removing it from the server. This allows for recovery when needed but still protects it from being accessed by unauthorized users.

Mitigating risk from managed service providers

The final sheet, “Mitigate Risks from Managed Service Providers in Cloud Environments,” is designed to help create more awareness regarding managed service providers (MSPs) being regular targets of malicious actors backed by nation-states.

There are also many misunderstandings about compliance with regulation standards when organizations choose to partner with cloud service providers. Companies need to have a clear understanding of shared responsibility principles and make sure their partnerships place a high priority on data security.

The sheet explains that organizations should have pre-established auditing mechanisms in place that include cloud-native data logging and monitoring. These help organizations better understand, control and secure the actions their MSPs are taking on behalf of the organization.

Embrace proactive cloud security

For years, the CISA and NSA have stressed that companies should take charge of cybersecurity readiness when working with MSPs in the cloud. By following the guidance of these CSIs, organizations can make sure they’re applying the latest best practices that will minimize their attack surface and improve their ability to successfully recover from cloud security breaches.

The post New cybersecurity sheets from CISA and NSA: An overview appeared first on Security Intelligence.

Security teams today are facing increased challenges due to the remote and hybrid workforce expansion in the wake of COVID-19. Teams that were already struggling with too many tools and too much data are finding it even more difficult to collaborate and communicate as employees have moved to a virtual security operations center (SOC) model while addressing an increasing number of threats. 

Disconnected teams accelerate the need for an open and connected platform approach to security . Adopting this type of approach can maximize investments by bringing new and existing security tools together, make SOC analysts more productive by moving their workflow into one place, and provide flexibility for organizations as their IT and security programs change. Our vision for a next-generation, open and integrated security platform  is built around three key tenets:

1. Open architecture: With the growing number of different tools and cloud platforms that organizations are using today, a next-gen security platform must be open enough to easily work with different tools from different vendors. Consolidating existing tools or moving data is often too expensive and complex to undertake, but adopting a platform that is based on open-source technology and backed by an open standards body allows teams to maximize existing investments by bringing all tools together in a standardized way.
2. Centralized hub: SOC analysts can improve their productivity with one primary system of record to manage their workflows. A centralized hub on top of an open architecture provides a way to fuse people, process and technology. This enables analysts to move out of the individual tools they use and streamline their work into one place while still providing the valuable data from the existing tools and decreasing the need to train the entire SOC on all of the tools deployed. The goal is to automatically put the right information in front of the right person at the right time to drive effective and decisive resolution.
3. Flexible deployment: Most organizations are using multiple clouds and on-premises solutions to manage their security and IT environments. And each is typically in the midst of their own unique journey to the cloud. A next-gen security platform that can deploy anywhere gives businesses the flexibility to choose what’s best now, and in the future, while avoiding lock-in to a particular deployment model.

SOAR is at the core of a next-gen security platform

Security orchestration, automation and response (SOAR) solutions are built on four engines as defined by Gartner: workflow and collaboration, ticket and case management, orchestration and automation, and threat intelligence management. The fusion of these capabilities improves SOC productivity and incident response (IR) times by bringing together people, process and technology. As such, these engines also provide an ideal basis for a robust security stack. Indeed, SOAR capabilities based on an open architecture and with a flexible, hybrid cloud deployment is the ideal approach for a security platform that fulfills this vision.

Placing SOAR at the heart of a security platform helps teams extend and maximize value across the ecosystem and to any security process while working in a centralized, coordinated manner. Incorporating SOAR capabilities into a next-gen security platform provides a foundation that will deliver several benefits.

Better communication within and outside the security team

Any SOC, especially a virtual one, requires seamless collaboration to guide responses and organize tasks — this is a key capability of a SOAR platform. Rather than starting from scratch, teams can work intelligently by following workflows embedded within dynamic playbooks. Furthermore, security teams can leverage the workflow and collaboration engine of SOAR to communicate with key players in different functions, such as IT, legal, HR or PR, helping to facilitate a coordinated and efficient response.

Improved efficiency with centralized case management

SOC analysts gain efficiencies from case management capabilities that can be managed from the centralized hub of a SOAR solution, eliminating the need to switch between multiple tools and dashboards. When case management is extended beyond the SOAR solution and into a broader security platform, it provides analysts with a common format to use across all connected capabilities. A strong case management function will also include dashboard and reporting capabilities to track metrics and KPIs, highlight trends and gaps, and elevate the business value of the SOC.

Maximum depth and breadth of the ecosystem

Security teams can maximize the depth and breadth of their ecosystems through an open architecture. An open, standards-based approach allows SOC teams to leverage the capabilities of a diverse ecosystem through integrations across a wide variety of data sources and tools and to capitalize on existing investments. The orchestration of these technologies extends SOAR capabilities while providing security analysts greater visibility into the ecosystem.

Placing SOAR at the heart of a next-gen platform allows customers to extend SOAR benefits beyond the incident response process for which SOAR was created to include any security process, such as vulnerability management, identity management, DevSecOps and more. This not only logically extends this investment to generate additional ROI but also yields KPIs about these processes, which can be used to drive continuous improvement and transform security’s relationship to the rest of the organization.

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How well are security leaders sleeping at night? According to a recent Gigamon report, it appears that many cyber professionals are restless and worried.

In the report, 50% of IT and security leaders surveyed lack confidence in knowing where their most sensitive data is stored and how it’s secured. Meanwhile, another 56% of respondents say undiscovered blind spots being exploited is the leading concern making them restless.

The report reveals the ongoing need for improved cloud and hybrid cloud security. Solutions to reveal blind spot vulnerabilities are urgently necessary as well.

Strong cloud and hybrid cloud security strategy needed

The worries exposed in the Gigamon report aren’t due to an active imagination on the part of cyber pros. Attacks are bombarding the security front lines. The report cites that 90% of those surveyed have suffered a data breach in the last 18 months.

As per the report, many IT and security teams lack critical visibility across data in motion from on-premises to the cloud. And they may not acknowledge these blind spots precisely because they can’t see them.

To manage a cohesive hybrid, multi-cloud security program, teams clearly need to establish visibility and control. This means integrating the appropriate controls, orchestrating workload deployment and establishing effective threat management.

Some solutions involve both cloud-native security controls and secure-by-design methodology. Furthermore, security orchestration and automation should be established to beef up protection further.

Where’s your data?

The continued struggle with data location has also been impacted by regulatory action. For example, the GDPR requires that users’ personal data and privacy be adequately protected by organizations that gather, process and store that data.

All this has given rise to concerns about data residency (data must be stored where it’s collected), data localization (data must remain in a specific place) and data sovereignty (rights and control over data based on jurisdiction).

However, cloud data residency is complicated by how cloud resources are deployed and used. For example, with dynamic cloud provisioning, resources are allocated upon demand, which can increase the attack surface. Furthermore, transient microservices in the cloud can result in data access and movement that is hard to detect and monitor.

Given these concerns, how can a security pro get any rest at all?

Know your data’s whereabouts

Ensuring data residency relies on two critical capabilities: localization and compliance monitoring. Localization technology detects the whereabouts of data, its copies and any movement within the cloud. Compliance monitoring technology centralizes, analyzes and reports on the adherence of cloud environments to regulatory requirements.

A Data Security Posture Management (DSPM) platform offers these capabilities by enhancing visibility into user activities and behavioral risks, aiding organizations in regulatory compliance. DSPM identifies the location of data and its copies stored in the cloud. DSPM also tracks data flows to and from cloud resources that may pose security risks.

Exposing data blind spots

What about those blind spots keeping security teams up at night? Attack Surface Management (ASM) can help by continuously monitoring IT infrastructure to detect blind spots and remediate potential points of attack.

This may involve deploying network monitoring tools capable of inspecting encrypted traffic, implementing cloud-native security controls and integrating cloud SIEM systems to correlate security events across on-premises and cloud environments.

Additionally, organizations should regularly assess their attack surface and adjust security measures accordingly to adapt to evolving threats and infrastructure changes.

The four core processes in attack surface management include:

1. Asset discovery: Automatically scans for entry points. Assets include computers, IoT devices, databases, shadow IT and third-party SaaS apps.
2. Classification and prioritization: Assigns a risk score based on the probability of attackers targeting each asset. Teams can categorize the risks and establish a plan of action to fix issues.
3. Remediation: Involves fixing issues with operating system patches, debugging or enhancing data encryption.
4. Monitoring: Continuous scanning for new vulnerabilities and remediating attack vectors in real time.

Security teams want peace of mind. Solutions such as cloud security strategy services and attack surface management just might help them rest a bit easier.

The post Cloud security uncertainty: Do you know where your data is? appeared first on Security Intelligence.

Over a decade since its advent, cloud computing continues to enable organizational agility through scalability, efficiency and resilience. As clients shift from early experiments to strategic workloads, persistent security gaps demand urgent attention even as providers expand infrastructure safeguards.

The prevalence of cloud-native services has grown exponentially over the past decade, with cloud providers consistently introducing a multitude of new services at an impressive pace. Now, the contemporary cloud environment is not only larger but also more diverse. Unfortunately, that size and complexity mean that the prevalence of knowledge gaps in cloud security has also increased to match.

A focus on user error

While continuous advancements are enhancing the security of cloud infrastructure, challenges persist in securing client cloud environments. The complexity of cloud security is exacerbated as organizations with varying levels of cloud dependency and maturity encounter unexpected problems on their journey. As cloud usage intensifies, new issues come to light.

According to Gartner, through 2025, “99% of cloud security failures will be the customer’s fault.” This assertion suggests that despite the inherent security measures in the cloud, security lapses predominantly stem from how clients use and safeguard their cloud resources. This perspective has led to a somewhat accusatory stance, with the onus placed squarely on clients for the outcomes of security breaches as spelled out in the cloud security shared responsibility model.

This is hardly a new issue. Even with the swift advancements in technology characterizing modern hyperscale cloud environments, security misconfigurations have been a predominant concern in cloud security for at least a decade — if not longer.

Misconfigurations: The enduring threat within

Today, misconfiguration continues to be a fundamental cause of numerous cloud security incidents. In a decade marked by significant technological progress and innovation in cloud computing, this simple security failure has endured.

Navigating cloud security is complex. As organizations enhance their cloud maturity, they inevitably encounter new challenges. Increased use of cloud services leads to the discovery of novel issues, perpetuating a cycle of continuous adaptation and problem-solving in the cloud domain.

The familiarity with problems and the struggle to resolve them is a daunting reality in cloud security. It’s a common and unsettling observation that, while cloud misconfigurations are not particularly challenging to identify, remediation in many environments is considerably difficult. This difficulty is especially pronounced in organizations that have not integrated security into their DevOps processes but continue to push workloads into the cloud.

In a recent example of these challenges, a healthcare provider knew that misconfigured cloud buckets posed severe data leakage and compliance risks. Yet it struggled to remediate gaps as budget constraints and coordination breakdowns across departments hindered consolidating configurations at scale. The organization had access to cloud security posture management (CSPM) tools, but inadequate implementation capacity and technical debt imposed severe obstacles to actionable improvement. Consequently, its inability to address these security lapses led to a critical data breach that exposed sensitive patient data. This incident not only underscored the importance of robust cloud security measures but also reiterated the grave repercussions of not remediating known security weaknesses.

The data breach highlights the complex barriers between risk awareness and risk reduction. It also underscores conflicts between security and internal client incentives fighting for limited IT resources. Another crucial lesson from this example is that the mere presence of CSPM tools is insufficient for effective security management. The effectiveness of these tools is contingent upon a well-defined implementation strategy. This strategy should encompass processes that not only utilize CSPM tools effectively but also align with and enhance the organization’s existing operational processes.

Essential to this strategy is the establishment of integrations that promote automation and uniformity in addressing security vulnerabilities and breaches. A healthcare data breach such as this one highlights the importance of a strategic approach to tool utilization, emphasizing the need for integration of CSPM tools into existing processes and the creation of automated systems to effectively manage cloud security risks.

Bridging persistent divides in the shared model

Central to cloud security is the shared responsibility model, where providers secure the underlying infrastructure while clients handle identities, configurations and data security. In practice, the model has some shortcomings:

• Clients frequently misjudge the handoff point between provider and user duties
• Clients trust providers to handle critical security tasks by default
• Clients lack the expertise and tools to implement complex security controls.

Additionally, there’s often confusion around default security settings, leading to mismatches between CSP native security offerings and customer security requirements. This complexity is even more pronounced in Platform-as-a-Service (PaaS) environments. The involvement of multiple parties, such as resellers or other cloud service providers, further muddles responsibilities and leads to security oversights. There are also areas where the division of security responsibilities is inherently ambiguous, like in threat detection, necessitating close cooperation between clients and providers.

Extreme cases, such as subpoenas or provider-originated security breaches, test the limits of the model. These challenges underscore the need for a deeper discussion about improving collaboration between providers and clients. Reliance on vendor documentation is insufficient as configurations grow more complex, spanning multiple cloud services and third parties. Joint ownership of security outcomes focused on shared fate rather than fragmented duties can close persistent gaps.

This issue is further exacerbated if clients depend on multiple cloud providers within their IT ecosystem, blurring the lines of responsibility between the various providers and the client. Ideally, a client considers the available cloud-native services and how they can be leveraged with third-party tools to extend security policy into the cloud.

Embedding security: From roadblock to roadmap

The terms SecDevOps and DevSecOps highlight a crucial concept: Excluding security from DevOps processes can leave an organization’s cloud infrastructure exposed. This makes it important to integrate a robust security framework within both the development and operational phases of cloud-based systems, ensuring a more secure and resilient cloud environment.

There is a lot of buzz around “DevSecOps,” but the real challenge is the practical integration of security and development. It’s a harsh reality that security and engineering often have conflicting goals. This tension is partly a result of organizational structures and market dynamics. Developers prioritize product development to drive revenue growth, while security is viewed through the lens of preventing revenue loss. Their goals are fundamentally misaligned: developers seek speed and innovation, whereas security emphasizes risk mitigation and control.

The shift to cloud computing has exacerbated this tension. Previously, IT teams, who had a better rapport with security teams as fellow cost centers, managed infrastructure deployment. However, cloud adoption has deeply entwined infrastructure with product development, shifting from a cost center to a line of business. This evolution is evident in the increasing investments in data infrastructure modernization, which is crucial to product strategy.

In a cloud-centric world, successful security solutions must offer seamless integration into DevOps workflows. These solutions should provide comprehensive visibility and control without necessitating significant collaboration or intervention from DevOps teams. The goal is to create an environment where security is embedded in the development process from the start, aligning with the speed and agility of cloud-based workflows.

Embracing the value of security

As the market evolves, there’s an increasing recognition of the need for both infrastructure and security to be integral components of the product value chain. This realization is leading to a gradual shift in how security products are designed and marketed. The future likely holds a more integrated approach where security and infrastructure are not just aligned but are co-dependent, each playing a critical role in the overall product strategy. This shift represents a significant change from the traditional view of security as a cost center, moving towards a model where security adds value to product development and deployment.

The journey of cloud-native application development is intricate, with security the common thread that runs through every stage. By embedding a DevSecOps approach, organizations can not only safeguard their applications and data but also build a resilient, secure and compliant cloud environment ready to face the challenges of today’s digital world.

Infrastructure-as-Code (IaC) is a pivotal concept in this evolution. IaC represents a significant shift, enabling the management of infrastructure through machine-readable files rather than traditional physical hardware setups. This method offers consistency and repeatability, crucial for upholding security standards. Concurrently, policy-as-code is revolutionizing the way security rules and compliance requirements are managed, allowing for automated policy enforcement across the infrastructure. This ensures that security measures are embedded from the start, promoting a proactive security posture.

For cloud security to be effective in this changing landscape, it must integrate seamlessly into DevOps workflows, offering visibility and control without burdening DevOps teams. The objective is to embed security within the development lifecycle, aligning it with the dynamic nature of cloud computing.

An imperative for collective responsibility

In the decade since cloud computing overhauled organizational infrastructure strategies, both providers and clients have made tremendous progress in securing an exponentially expanding attack surface. However, stubborn gaps rooted in fragmentation of accountability, lack of infrastructure security capacity and unaligned DevSecOps incentives present severe threats to enterprises entrusting their most valuable data to the cloud.

Cloud security is not just a technical challenge but a strategic imperative to be used as a business enabler. The effective integration of IaC, policy-as-code and DevSecOps principles is key to ensuring robust and adaptable security in cloud environments. As organizations continue to migrate and expand their cloud infrastructure, embracing these methodologies will be crucial in safeguarding their digital assets and maintaining a competitive advantage in an increasingly cloud-centric world.

A major advantage of this evolving landscape is the ability for developers to concentrate on their core tasks, such as solving business problems and driving innovation, without being overburdened by security concerns. The separation of responsibilities, where a dedicated team ensures that the cloud controls are compliant and secure, has led to a more efficient and focused working environment for developers. They benefit from quicker access to approved cloud objects, knowing that the integration and security aspects are being handled efficiently and effectively by specialized teams. This division of labor allows developers to remain focused on their primary objectives, with security seamlessly integrated into the background.

A new era of cloud security

This new approach to cloud security emphasizes the importance of being unobtrusive yet effective. The ideal scenario is one where security measures are so well integrated and managed that they become virtually invisible, not hindering the developers’ workflows but silently protecting the integrity of the systems. The aim is to create a secure cloud environment where security operations do not impede but rather empower developers, allowing them to innovate freely while ensuring robust security measures are in place and aligned with corporate policies. This harmonious balance is essential for organizations looking to thrive in an increasingly cloud-centric world, making cloud security a critical pillar of their overall strategy.

Navigating this complex security landscape often requires the expertise of a services integrator specialized in cloud application development and security, such as IBM Security. Such a partner can offer both managed services and advisory expertise, tailoring cloud-native security controls and third-party tools to align with the client’s current infrastructure and future objectives. That guidance can be pivotal in ensuring a seamless and secure transition to the cloud, bolstered by best practices in security.

The road ahead is challenging but navigable. With improved visibility into constraints and empathy towards objectives across historically siloed personnel, organizations can translate principle-level awareness of cloud security risks into operational resilience secured by coordinated action.

Want to learn more about cybersecurity services for AWS? Visit the Security Services for AWS page on IBM. You can also explore more on cybersecurity services for Microsoft Azure here.

The post Cloud security evolution: Years of progress and challenges appeared first on Security Intelligence.

Cloud environments were frequent targets for cyber attackers in 2023. Eighty-two percent of breaches that involved data stored in the cloud were in public, private or multi-cloud environments. Attackers gained the most access to multi-cloud environments, with 39% of breaches spanning multi-cloud environments because of the more complicated security issues. The cost of these cloud breaches totaled $4.75 million, higher than the average cost of $4.45 million for all data breaches.

The reason for this high cost is not only the penalties paid for the data breaches but also the amount of time (mean time to identify, or MTTI) it takes to discover and remediate the breach. The typical time in days that it takes to identify a breach is significant across all configurations, with the worst being multi-cloud and hybrid-cloud environments.

The figure above is measured in days. (Source: IBM)

These statistics are not only alarming but could conceivably be catastrophic, depending on the number and type of breaches that occur. They clearly spell out the compelling need for data protection in cloud applications and infrastructure.

Just how popular is the cloud?

According to a study published by G2.com in April 2023:

Cloud-first is the mantra

• All companies use at least one public or private cloud
• By 2025, 85% of organizations will be “cloud first”
• Over 60% of all corporate data is in cloud storage
• 100 trillion gigabytes of data will be stored in the cloud by 2025.

Multi-cloud is popular

• 98% of enterprises use or plan to use at least two cloud infrastructure providers
• 31% of enterprises have four or more cloud infrastructure providers
• Nearly 9 out of 10 companies report having a multi-cloud strategy.

Hybrid cloud is on the rise

• Nearly 8 of 10 companies use multiple public clouds and 60% use more than one private cloud
• 56% of companies with more than $500 million in revenue have adopted a hybrid cloud.

If we apply a conservative estimate that 33% of 100 trillion gigabytes of data stored in the cloud is unprotected, that means that 33 trillion gigabytes are constantly at risk of being breached.

The emerging solution

Cloud-native data protection is a technology that protects data stored in and moving through cloud infrastructure by:

1. Identifying where it’s located
2. Identifying shadow copies of sensitive data
3. Identifying data movement within and across multi-cloud and hybrid-cloud infrastructure.

To qualify as cloud-native and to handle the rapid movement and complexity of cloud services, the data protection technology should be implemented with cloud infrastructure and use cloud methodologies, such as containers, Kubernetes and microservices.

The name for this capability is data security posture management (DSPM), and it satisfies the requirements listed above for public, private, multi-cloud and hybrid-cloud environments.

What is cloud-native?

Cloud-native applications consist of multiple small, interdependent services called microservices. They are composed of:

• Application programming interfaces (APIs), which bring loosely coupled microservices together
• Service mesh, which manages the communication between multiple microservices
• Containers, which are the application software components that pack the microservice code and other required files in cloud-native systems
• Container Orchestrator/Manager, such as Kubernetes, which facilitates declarative container configuration, such as pods, and automation. 

Cloud and data protection impact

Data breaches certainly have the potential to slow cloud migration and innovation. How many breaches, after all, will users be willing to endure before demanding more comprehensive protection? Data privacy laws, such as the General Data Protection Regulation (GDPR), are also driving protection by levying fines on entities that don’t adequately protect data privacy.

Every application and website user appreciates cloud applications’ innovation and performance, including the personalization that cloud-native and artificial intelligence (AI) technologies facilitate. But that enthusiasm will likely ebb if data breaches escalate. Without more immediate attention to data protection, users may demand immediate, increased levels of accountability that could slow innovation.

DSPM to the rescue

To assuage these concerns, DSPM has emerged to address cloud data protection. DSPM identifies all repositories of “at risk” data within public, private, multi-cloud and hybrid-cloud infrastructure, which includes relational databases, Big Data stores, in-memory databases, Software-as-as-Service (SaaS) applications and shadow data.

That means DSPM finds data in any cloud storage repository, including data copied for any purpose outside a database or files such as log files. It also tracks data as it moves through cloud components to ensure that if data is moved, the organization knows about it and can implement remedial actions if needed.

But the most amazing part is that DSPM is incredibly easy to use. It automatically discovers data, catalogs where data resides so that shadow data can be identified and sends alerts about data vulnerabilities so that remedial actions can be taken as needed.

The compelling need for cloud-native data protection

Cloud-native data protection is needed to protect the wealth of generated data and traversing cloud infrastructure. The implementation needs to be cloud-native so that data in all multi-cloud repositories can be seen. In addition, cloud-native implementation enables organizations to see where data moves through applications built with cloud components, such as containers, APIs and service meshes, to get to the next storage location.

DSPM also belies the notion that cloud data security is hard to use and consumes too many resources to be effective. Using automated discovery, cloud-native DSPM automatically identifies sensitive data, shadow data, data locality and point-to-point data movement through cloud infrastructure and application components.

DSPM is easy to use, finds data locations and maps them and monitors data as it moves through the (multi-)cloud infrastructure. IBM Security Guardium Insights SaaS DSPM embodies all of the capabilities listed above.

Learn more on IBM Guardium Insights SaaS DSPM or sign up to try it for free now.

The post The compelling need for cloud-native data protection appeared first on Security Intelligence.

As organizations modernize their IT infrastructure and increase adoption of cloud services, security teams face new challenges in terms of staffing, budgets and technologies. To keep pace, security programs must evolve to secure modern IT environments against fast-evolving threats with constrained resources. This will require rethinking traditional security strategies and focusing investments on capabilities like cloud security, AI-powered defense and skills development. The path forward calls on security teams to be agile, innovative and strategic amidst the changes in technology and cyber risks.

To meet these security demands, security teams must focus on three critical transformations:

1. Evolution from closed vendor ecosystems to open, collaborative, community-powered defense
2. Scaling security expertise with AI and automation
3. Evolution from tool-focused defense to analyst-powered outcomes

One of the most effective steps toward modernizing a security operations program is upgrading the core SIEM platform. As the central nervous system for SOC teams, the SIEM collects, correlates and analyzes data from across the IT environment to detect threats. Optimizing this capability by implementing a cloud-native SIEM or augmenting an on-premises system lays the digital foundation needed to scale security efforts.

With a high-fidelity view of security alerts and events via an upgraded SIEM, organizations gain the visibility and context required to identify and respond to cyber risks no matter the source. Prioritizing improvements here accelerates the transformation of siloed security practices into an integrated, intelligence-driven function poised to address both current and emerging challenges.

Open defense: Finding the real “threat needles” hidden in the “security-data haystack”

The explosion of data has increased the attack surface—a most significant side effect that has costly ripple effects. More data. More alerts. More time needed to sift through alerts.

The SIEM plays a critical role in analyzing this data—however, the reality of sending this volume of data to the SIEM for analysis is becoming increasingly challenging, particularly across multiple clouds. In some cases, sending all of the data is not necessary. With the evolution of cloud, and identity and data security tools in the cloud, there is often only a need to collect alerts from these systems and import those into the SIEM, as opposed to ingesting all data.

Today’s SIEMs should be designed around open standards and technologies so they can easily collect only key insights, while still providing the security team with access to the underlying telemetry data when needed.

In many cases, no such detection is required; in other cases, a security team only needs to collect data to do further specific threat analysis. In these cases, a SIEM with real-time data collection, data warehousing capabilities designed for analysis of cloud-scale data, optimized for real-time analytics and sub-second search times is the solution. Organizations need access to their data on-premises and in the cloud without dealing with vendor and data locking.

This open approach to SIEM helps organizations leverage existing investments in data lakes, logging platforms and detection technologies. It also ensures that organizations have the flexibility they need to choose the right data retention and security tools as their security infrastructure matures.

However, increased visibility into the data is only one part of the solution. Security teams need accurate and current detection logic to find threats because security teams are currently facing challenges in their skills to detect threats in a timely manner. Incorporating regularly updated threat intelligence enables the analyst to accelerate their threat detection. And, leveraging a common, shared language for detection rules like SIGMA, allows clients to quickly import new, validated detections directly crowdsourced from the security community as threats evolve.

AI and automation to accelerate threat detection and response

Most organizations are detecting malicious behaviors in a SIEM or other threat-detection technologies such as EDR, but in fact, SOC professionals get to less than half (49%) of the alerts that they’re supposed to review within a typical workday, according to a recent global survey. Leveraging automation and AI ensures transparency and provenance in recommendations and insights that can help security teams address high-priority alerts and deliver desired outcomes.

To do this, a SIEM needs to employ innovative risk-based analytics and automated investigation powered by graph analytics, threat intelligence and insights, federated search, and artificial intelligence. Effective SIEM platforms must leverage artificial intelligence to augment human cognition. Self-tuning capabilities reduce noisy alerts to focus analyst attention where it’s needed most. Virtual assistance can help handle routine triage to allow security experts to pursue strategic initiatives and robust machine learning models can uncover hidden attack patterns and incidents that rules-based systems miss. Some of the most advanced SIEMs enrich and correlate findings from across an organization’s environment so analytics are automatically focused on the attacks that matter most.

In order to build the required trust with security teams, a SIEM needs to provide transparency and provenance in its recommendations and insights. By including explainability into how each assessment was made, security analysts can have the confidence to trust recommendations and act more quickly and decisively on threats in their environment.

Another aspect vendors need to consider when developing a SIEM for today is the shift of moving the decisions and response actions to the analysts performing initial alert analysis from the responder. In many cases, they are looking to fully automate where balance of risk is right for the organization. Such processes and decisions are traditionally coordinated and tailored appropriately in a separate SOAR system, and in some cases with a different team. Today’s SIEM needs to be able to enable a more agile shift left to incorporate full SOAR capabilities in the SIEM workflow and UX. This approach enables organizations to almost fully automate response processes based on their balance of risk and, where needed, introduce the security team into the process to verify the recommended actions.

Evolving from tool-focused to analyst-focused defense

Early SIEM platforms centered on collecting and correlating vast streams of security data. These first-generation systems excelled at log aggregation but overloaded analysts with excessive alerts rife with false positives. Attempting to keep pace, teams added new tools to manage incidents, track threats and automate tasks. But this tech-driven approach created complex, fragmented environments that diminished productivity.

Modern SIEM solutions shift focus to the human analyst’s experience throughout the threat lifecycle. Rather than produce more data points, next-generation platforms leverage AI to find signals in the noise. Cloud-based analytics uncover hard-to-identify attack patterns to feed predictive capabilities and enrich findings from across an organization’s environment so analysts can focus on the attacks that matter most. To effectively work inside the analyst workflow, open architectures and integrated system visibility must be embedded in every SIEM.

In the instance of a modern SIEM, the tools and technologies work to serve the analyst—and not the other way around.

Introducing the new cloud-native IBM QRadar SIEM— thoughtfully engineered to help analysts succeed

At IBM, we recognize that having the most powerful technology means nothing if it burdens the analyst with complexity. We also recognize that SIEM technologies have often promised to be the “single pane of glass” into an organization’s environment—a promise that our industry needs fulfilled.

That’s why we built the new cloud-native QRadar SIEM with the analyst in mind. QRadar SIEM leverages a new user interface that fuses the primary workflows from threat intelligence, SIEM, SOAR and EDR into a single, seamless workflow. Not only does this deliver significant productivity improvements but it also removes the burden of switching between tools, dealing with false positives and inefficient workflows. When analysts have the right tools and context, they can move with speed and precision to stop sophisticated attacks.

This new cloud-native edition of QRadar SIEM not only builds on the data collection and threat detection of the current QRadar SIEM edition, but it also includes all the elasticity, scalability and resiliency properties of a cloud-native architecture. With openness, enterprise-grade AI and automation, and a focus on the analyst, QRadar SIEM (Cloud-Native SaaS) can help maximize your security team’s time and talent, ultimately delivering better security outcomes.

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Cloud computing has become an integral part of IT infrastructure for businesses of all sizes, providing on-demand access to a wide range of services and resources. The evolution of cloud computing has been driven by the need for more efficient, scalable and cost-effective ways to deliver computing resources.

Cloud computing enables on-demand access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications and services) over the internet. Instead of owning and maintaining physical hardware and infrastructure, users can leverage cloud computing services provided by third-party providers.

Cloud service and deployment models

Cloud computing is commonly categorized into service and deployment models:

Service models

1. Infrastructure as a Service (IaaS): Provides virtualized computing resources over the internet. Users can rent virtual machines and storage and networking components.
2. Platform as a Service (PaaS): Offers a platform that includes tools and services for application development, testing and deployment. Users can focus on building applications without managing the underlying infrastructure.
3. Software as a Service (SaaS): Delivers software applications over the internet on a subscription basis. Users access the software through a web browser without worrying about installation or maintenance.

Deployment models

1. Public cloud: A third-party cloud service provider owns and operates resources and makes them available to the general public. Some providers include Amazon Web Services (AWS), Microsoft Azure and Google Cloud Platform.
2. Private cloud: A single organization exclusively uses resources. Either the organization or a third-party provider can manage the infrastructure, which can be located on-premises or off-site.
3. Hybrid cloud: Combines public and private cloud models to allow data and applications to be shared between them. This provides greater flexibility and optimization of existing resources and infrastructure.

4 common cloud attack scenarios

Unfortunately, every rapidly growing industry attracts not only enthusiastic entrepreneurs but also malicious actors whose goal is to take advantage of any security holes that would be unable to defend against various attacks. Here are some examples of common attack scenarios in the cloud.

1. DDoS attacks

A distributed denial of service (DDoS) attack occurs when a web application is overloaded with a high volume of traffic. DDoS protection services, like AWS Shield, can mitigate such attacks.

AWS Shield uses machine learning algorithms to analyze incoming traffic, identify patterns indicative of a DDoS attack and take action to stop the attack.

2. Data breaches

A data breach involves exploiting vulnerabilities to access and exfiltrate sensitive data. But regularly updating software, encrypting sensitive data, monitoring for unusual activity and building a good incident response can help prevent data breaches.

Below is an incident response example code (AWS Lambda for Incident Response) in Python (Boto3 is a Python software development kit [SDK] for AWS).

3. Man-in-the-middle attacks

A man-in-the-middle (MitM) attack occurs when communication between two parties is intercepted for malicious intent. The use of encryption (SSL/TLS) and implementing secure communication protocols can help prevent a MitM attack. Without encryption, data transmitted over the network can be intercepted.

The code below is an example of encrypting S3 Objects with AWS SDK for Python-Boto3.

4. Brute force attacks

A brute force attack is a hacking method that uses trial and error to crack passwords, login credentials and encryption keys. It is a simple yet reliable tactic for gaining unauthorized access to individual accounts and organizational systems and networks.

AWS CloudWatch Alarms can provide logging and monitoring services where repeated login attempts might go unnoticed.

Cloud configuration security best practices

Security in cloud computing involves implementing measures to protect data, applications and infrastructure in a cloud environment from potential threats. Here are some best practices in key areas of cloud configurations in AWS and Azure associated with securing cloud environments.

 AWS

 Identity and access management (IAM):

• Use the principle of least privilege when assigning permissions to users, roles and groups
• Regularly review and audit IAM policies to align with business requirements
• Enable multi-factor authentication (MFA) for enhanced user authentication.

Example AWS IAM policy:

If IAM policies are not properly configured, an attacker might gain access to sensitive resources.

VPC (virtual private cloud) configuration:

• Utilize separate subnets for public and private resources.

 Example code (AWS CloudFormation):

S3 Bucket Security:

• Regularly audit and review access controls for S3 buckets
• Enable versioning and logging to track changes and access to objects
• Consider using S3 bucket policies to control access at the bucket level
• Enforce server-side encryption for S3 buckets.

Example code (AWS CLI):

Azure

Azure role-based access control (RBAC):

• Assign the principle of least privilege using Azure RBAC.

 Example code (Azure PowerShell):

Azure Blob storage security:

• Enable Blob storage encryption.

 Example code (Azure PowerShell):

 Azure virtual network:

• Implement network security groups (NSGs) for access control.

 Example code (Azure Resource Manager Template):

Keeping digital assets secure in the cloud

Securing cloud configurations is essential to safeguard digital assets and maintain a resilient cybersecurity posture. Organizations should focus on continuous monitoring, compliance checks and proactive incident response planning to address the dynamic nature of cyber threats in the cloud.

In addition, implementing the principles of least privilege, encryption, identity and access management and network security best practices not only protects the cloud environment against potential vulnerabilities but also contributes to a culture of security awareness and responsiveness within the organization.

As cloud computing continues to evolve, organizations should commit to staying ahead of emerging security challenges and adapting configurations to maintain a resilient and secure digital presence.

Not sure how to start? IBM Security has a range of cloud security services to protect your cloud environment.

The post Best practices for cloud configuration security appeared first on Security Intelligence.

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Cloud security is a buzzword in the world of technology these days — but not without good reason. Endpoint security is now one of the major concerns for businesses across the world. With ever-increasing incidents of data thefts and security breaches, it has become essential for companies to use efficient endpoint security for all their endpoints to prevent any loss of data. Security breaches can lead to billions of dollars worth of loss, not to mention the negative press in the business world.

This is why it is vital for companies to use cutting-edge endpoint security technology for their cloud computing systems. If you are working with cloud systems in any capacity, you must also use cloud security to safeguard data breaches.

However, before you develop a good understanding of cloud security, the first and most important step is learning about cloud computing and its essential properties.

What is cloud computing?

Cloud computing can be best described as a range of hosted services offered through the internet. It replaces the need to store all computing infrastructure in a physical server environment, a physical computer or an on-premises data center. Cloud computing works with off-site hardware for hosting different types of services and encompasses software systems and storage solutions.

This flexible cloud model offers a range of strategic benefits for the users, including:

• Easy scalability
• Quick start deployment
• Reduced costs for initial setup and long-term use.

When an organization has extensive privacy and compliance requirements, it can work with hybrid cloud infrastructure, which makes use of both cloud and physical computing ecosystems.

Because cloud computing works very differently from on-site hosting systems, it is necessary to protect the cloud environment using cloud security infrastructure. Through cloud security, it is possible to deal with the privacy and cybersecurity challenges posed by the cloud environment.

Cloud security involves everything used to safeguard sensitive data stored within the cloud. Using a variety of techniques, procedures, methods and controls, cloud security protects cloud applications and infrastructure from any kind of online abuse or unauthorized access.

Some cloud security aspects require more effort by the cloud customer than what cloud service providers can offer. This is particularly true for zero trust cloud architecture.

Endpoint security

Endpoint security has to do with the processes used for securing endpoints like desktops, laptops, servers and mobile devices from possible malware, unauthorized access and all other kinds of cybersecurity threats. As more and more companies work with cloud computing, endpoint security has increased in importance as it allows users to protect their cloud-based applications and data.

Endpoint security in a cloud environment is something that most modern organizations need to think about when they start adopting cloud-based services. Through endpoint security, it is possible to implement practices for protecting endpoint devices, like laptops, mobile devices and desktops. Within the cloud environment, the tools of endpoint security help to secure the devices connecting to the cloud-based services and applications.

Endpoint security for the cloud infrastructure involves multifaceted and complex processes that use different types of technologies and practices to ensure application and data security.

These are some essential features of cloud-based endpoint security:

• Endpoint protection. Cloud endpoint protection is carried out with security software like firewalls, antivirus tools and systems for intrusion detection and prevention. These programs help to protect the endpoints from numerous security threats. Endpoint protection in the cloud is often provided by cloud-based security experts who are trained mainly to protect the cloud-based endpoints.
• Data encryption. Through data encryption, it is possible to convert plain text into an unreadable format so that it is only possible to decrypt it with a secret key. Data encryption in the cloud is vital for protecting all kinds of sensitive data from being accessed by unauthorized parties. The endpoint security solutions for cloud systems often use data encryption as a standard security feature.
• Identity and access management (IAM). IAM functions as a critical element of endpoint security for cloud computing. IAM includes tools for managing user identities and access to cloud-based resources. It includes authorization, authentication and access control. Such functions are essential for ensuring the protection of sensitive applications and data in the cloud.
• Threat intelligence. Threat intelligence is a process that uses information about cyber threats to identify and prevent security breaches. Threat intelligence can help identify potential security vulnerabilities and threats in cloud-based endpoints. Endpoint security solutions for the cloud typically include threat intelligence features that offer real-time detection and prevention of threats.
• Compliance and governance. Compliance and governance functions are crucial aspects of cloud-based endpoint security. Organizations need to comply with different industry standards and regulations to ensure the privacy and security of cloud-based data systems and applications. The endpoint security solutions for cloud platforms typically include governance and compliance features to help organizations meet such requirements.

Endpoint security for the cloud is an essential feature of the cloud security infrastructure that organizations must implement for better security. By using endpoint security measures and systems in the cloud, organizations can ensure the privacy and security of cloud-based applications and data. It also helps to comply with the regulatory requirements and ensures protection against cyber threats.

Challenges and solutions to cloud-based endpoint security

As companies try to migrate their diverse data and operations into the cloud, the importance of endpoint security has increased for all kinds of cloud applications. Cloud infrastructure offers cost efficiency, flexibility and scalability and also presents a fresh range of challenges for securing the endpoints.

The following challenges are associated with cloud-based endpoint security:

1. Absence of physical control. A major difficulty in securing the endpoints within the cloud system is an absence of physical control over the devices. The cloud system is a completely virtual environment, and organizations cannot secure their devices physically as they are able to do with the traditional endpoints. As a result, it can be challenging for them to implement and preserve security controls.
2. The complexity of handling security requirements. Another distinct challenge associated with endpoint security in a cloud environment is the complexity and difficulty of maintaining security across numerous cloud services and providers. Organizations that work with multiple cloud providers and services have to make sure that each service is properly secured. This can be an arduous and time-consuming task.
3. Different risks. Cloud-based endpoints involve different risks compared to traditional endpoints and are typically more vulnerable to data breaches, malware infections and account takeover attacks. This is because the cloud-based systems and endpoints are highly accessible to attackers since they are based in a cloud environment.

Here are some solutions for endpoint security in the cloud:

1. Using endpoint protection platforms (EPPs). EPPs protect endpoints from different types of cyber threats. The EPPs are often deployed within the cloud environment. They can be integrated with many other cloud security solutions to provide complete endpoint security.
2. Implementing IAM systems. IAM systems can help organizations easily manage user identities and monitor access to cloud applications and services. In this way, IAM tools can prevent unauthorized access to the cloud-based endpoints.
3. Deploying cloud access security brokers (CASBs). CASBs serve as security solutions that can provide control and visibility over cloud-based services. The CASBs make it easier for organizations to monitor and secure cloud-based endpoints through the implementation of access controls and security policies.
4. Educating employees. It is important to invest in employee training and education when it comes to maintaining robust and strong endpoint security in the cloud. Organizations need to educate employees regarding the best practices for securing data and devices in the cloud environment. Such practices include installing security software, updating it regularly and avoiding risky online behavior.

Crucial components of cloud-based endpoint security

Implementing endpoint security solutions for cloud systems is a major challenge for organizations. Nevertheless, by consulting with the right cloud security service providers, businesses can mitigate risks and ensure robust endpoint security.

Organizations should leverage solutions such as EPPs, CASBs and IAM tools, and also educate employees regarding the best practices for securing their data and devices in the cloud environment. Having such tools and measures in place can make it easier for organizations to protect their diverse cloud-based endpoints and critical operations and data.

It is important to implement the following endpoint security systems in the cloud:

1. Robust protection against cyber threats. More often than not, cloud-based endpoints are vulnerable to cyber threats such as phishing attacks, malware and data breaches. Endpoint security in the cloud can make it easier for organizations to protect themselves by systematically monitoring malicious activities and preventing unauthorized access.
2. Compliance with regulations. Numerous industries have regulations for monitoring and protecting sensitive data, such as financial information and health care data. Using endpoint security in the cloud makes it easier for organizations to meet such regulations and steer clear of costly fines.
3. Maintaining optimum business continuity. If a data breach or cyberattack occurs, compromised cloud-based endpoints can result in lost revenue and significant downtime. Endpoint security systems within the cloud ensure smooth maintenance of business continuity by minimizing or preventing the impact of security breaches.

Best practices for endpoint security in the cloud

When implementing your organization’s endpoint security in the cloud, keep the following best practices in mind:

1. Implementing strong and reliable authentication measures. Having strong authentication measures like two-factor authentication can make it easier to prevent unauthorized access to cloud-based endpoints. Organizations must update their endpoint security systems regularly and patch the systems to address vulnerabilities.
2. Using endpoint detection and response (EDR) solutions. EDR systems and solutions are created to easily detect and systematically respond to various forms of advanced endpoint threats. By identifying and regulating threats before they spread through the whole cloud environment, EDR solutions can help keep your endpoints safe.
3. Managing and monitoring user activity. Through careful monitoring of user activity on cloud-based endpoints, it is possible to detect malicious activities and unauthorized access. Efficient user activity monitoring can assist in identifying the areas where it is necessary to implement additional security controls.
4. Updating and patching software regularly. Regularly patching cloud-based endpoints helps address vulnerabilities and ensures protection against known threats. Organizations need to implement a systematic and regular patching schedule as well as test the patches prior to deploying them within the production environments.
5. Educating employees. It is important to invest in employee training and education to maintain proper endpoint security in the cloud. Organizations need to educate employees regarding the best practices on cloud security to secure their data and devices. This involves installing security software, avoiding risky online behavior and reporting suspicious activity.

Organizations that regularly store and manage their applications and data in a cloud environment must focus on implementing endpoint security best practices. This can protect them against possible cyber threats, maintain business continuity and comply with regulations. Organizations can implement practices having strong authentication measures, monitoring all user activity, using high-end EDR solutions, regularly updating and patching security software and educating employees regarding strong endpoint security within the cloud. Following such endpoint security best practices can ensure the protection of the cloud-based endpoints so that critical operations and data can be safeguarded.

Critical security risks in the cloud environment?

The importance of cloud security has increased over the years. In that time, numerous enterprises have opted for cloud adoption when managing their data and applications. Unfortunately, many types of security challenges emerge while companies invest in cloud solutions. Some of these challenges include:

A more widespread threat landscape

Since many people use public cloud environments nowadays, this has increased the vulnerability of the cloud environment to data breaches as well as other critical security risks. When business entities fail to do their due diligence for security needs, they may leave their data open to criminal exploitation. In many instances, companies may not even realize their data has been stolen.

Lack of control over cloud security services

A major reason for the popularity of cloud adoption is that cloud service providers often handle security management, maintenance and upgrades. Even though this is a major benefit, it can severely limit the scope of an organization to exercise control over the way security is implemented and monitored.

Automation in DevOps

Cloud hosting brings with it the option to automate most of the continuous integration/continuous delivery (CI/CD) processes and DevOps that organizations employ to streamline their operations.

Weak access management

When organizations opt for cloud adoption, it is vital that they have a dedicated framework for managing access control. In most cases, they use a standard free-for-all arrangement that allows users more access than they actually need for their work. This can enhance the chances of security risks both internally and externally as cyber criminals may have access to the privileges of the users.

Inconsistent security features in complex environments

Numerous organizations work with a hybrid cloud environment or a multi-cloud environment, which uses several public and private cloud providers along with on-premise solutions. Such a situation can give rise to inconsistent use of security protocols, thus enhancing the chances of successful cyberattacks.

Compliance requirements

Even though a majority of the well-known cloud providers have tried to get security certifications for well-known cybersecurity frameworks, customers are still accountable for ensuring that their security systems and processes comply with major security protocols.

Six pillars of cloud security

Even though there are numerous differences between traditional security and cloud security, organizations can boost their security parameters against cyber threats in the cloud. This is why companies need to exercise due diligence when securing their cloud systems, just like in on-premises environments.

These six pillars of cloud security are crucial for securing the cloud:

1. Secure access controls. Implementing secure IAM protocols creates a robust security framework. Team members should only have the level of access to assets, systems and application programming interfaces they need to carry out their job responsibilities. When privileges increase, there should be higher levels of authentication needed to gain access. The employees need to take ownership of security and also use better password policies.
2. Zero trust network security controls. The mission-critical applications and assets used by the organization should be kept within strategically isolated parts of the cloud network. These can be virtual private cloud systems. By segregating the sensitive workloads from the ones that do not need data security protocols, it is possible to enforce micro-segmentation with strict security policies.
3. Change management. By working with change management protocols offered by the cloud security providers, it is possible to manage change and use compliance controls whenever changes are requested. This should also be done when new servers are provisioned or sensitive assets get changed or moved. Change management applications offer auditing functionality to users, which can help in monitoring unusual behavior and possible deviations from the protocol. This means the organization can investigate the problem and trigger automatic mitigation to correct the issue.
4. Web application firewall. A web application firewall (WAF) makes it easier to scrutinize traffic going in and out of servers and web applications. By monitoring and alerting administrators regarding any suspicious behavior, a WAF can strengthen endpoint security to avoid breaches.
5. Data protection. Enhanced data security is possible when an organization encrypts its data at all layers. There should also be security protocols for communication applications, file sharing and other areas within the environment where the organization stores, uses and transmits data.
6. Continuous monitoring. Numerous cloud security providers offer valuable insight into cloud-native logs, enabling comparison with internal logs taken from other security tools like asset management tools, vulnerability scanners, change management tools and insights from external threat intelligence. Such efforts increase the chances for rapid incident response and make it easier to implement remediation workflows.

Cloud-based endpoint security keeps your business secure

Cyber criminals are always looking for ways to attack endpoints and infiltrate servers while avoiding notice. Therefore, it is crucial that businesses invest in endpoint security so that they are able to prevent breaches.

Through endpoint security, it is possible to benefit from better data protection and encryption features that prevent criminals from achieving their nefarious purposes. Implementing cloud security features can secure data access, prevent infiltration and deliver benefits like better monitoring of user activity.

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